Core Insurance, Risk Management
Article | August 4, 2022
Automated claims processing, price comparison platforms, mobile bill paying—these are just some of the digital services that insurance customers expect and insurers want to provide. As the demand for digital skyrockets, so does the need for insurers to invest in IT. In the past seven years, the share of IT in total operating costs of property-and-casualty (P&C) insurers increased 22 percent. The rise of digital means technology is no longer a cost center. Rather, it is an asset that, if managed well, can increase growth and profitability.
But do these IT investments pay off? As the COVID-19 pandemic exacerbates already increasing cost pressures, insurers’ IT budgets are under scrutiny; they want to see the business impact of their IT investments.
Insurers with targeted IT investments achieve better growth and performance
Data from McKinsey’s Insurance 360° benchmarking survey provide strong evidence of the positive business impact of targeted IT investments. In fact, insurers that invest more in technology outpace competitors that don’t pursue targeted investments in business measures such as gross written premium (GWP) growth, return to shareholders, and expense and loss ratio (exhibit).
As an example, in life insurance, companies that invested more in IT saw a greater reduction in expense ratios (by 2.0 percentage points) and higher returns on technical reserves2 (1.7 percentage points) when compared with insurers with lower IT investments. Insurers achieved these outcomes within three to five years of making their investments.
For P&C insurers, those with high IT investments achieved approximately twice the top-line GWP growth of low IT investors. High IT investments also produced a greater reduction in combined ratios when compared with those with low IT investment.
Four areas for targeted IT investment
So what kinds of technology investments can help insurers achieve growth and improve productivity and performance? Investments in four areas are critical:
Marketing and sales: Marketing technology solutions can increase sales and processing efficiency, improve the quality of core customer-facing processes such as policy inquiries and policy applications, and improve customers’ overall experiences. McKinsey’s Insurance 360° benchmarking data show that tech investments in this category can facilitate top-line growth for P&C insurers by up to 20–40 percent; for life insurers, that growth could be 10–25 percent over a three- to five-year period.
Underwriting and pricing: Automated underwriting fraud detection can improve the likelihood that insurers correctly identify fraud and set accurate prices. A pricing tool kit that analyzes pricing across competitors and enables a flexible, more segmented market versus technical pricing further improves profit margins. Insurers that deploy these and other product, pricing, and underwriting technologies have seen improvements in their profit margins by 10–15 percent in P&C insurance and 3–5 percent in life insurance.
Policy servicing: Workflow automation, artificial intelligence–based decision support, and user experience technologies in policy servicing and within IT can improve the customer self-service experience and automate back-office processes, thus reducing IT and operations expenses. And state-of-the-art self-servicing options will reduce processing times and even improve customer experience. An analysis of programs for large-scale insurance IT modernization finds that insurers that deploy these and other product, pricing, and underwriting technologies have seen improvements in their profit margins by 5–10 percent in P&C insurance and 10–15 percent in life insurance.
Claims: P&C insurers can use automated case processing—machine-learning technology trained to process basic claims cases—to segment more complex cases and significantly improve claims accuracy. Combined with better partner integration and steering technologies embedded in a transformation of the claims operating model, such technologies can help P&C insurers improve profit margins by 25–40 percent, according to McKinsey analysis of large-scale IT modernization programs.
To realize the full value of IT investments, insurers must strategically allocate their resources and view tech as an asset, not a tool.
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Insurance Technology
Article | July 14, 2022
As AI becomes more deeply integrated into the industry, carriers must position themselves to respond to the changing business landscape. Insurance executives are expected to understand the factors driving this shift and how AI in insurance will impact claims, distribution, underwriting, and pricing. They can start to learn the skills and talent they need, embrace new technology in the insurance industry, and build the culture and perspective they need to be successful in the future insurance market with this grip.
While there are four types of levers that might help with productivity efforts—functional excellence, structural simplification, business transformation, and enterprise agility—insurers typically focus on the first two. Those levers are the foundation of efficient and effective operations, it isn't easy to leapfrog them. Traditional industry barriers are dissolving while technology advances and customer expectations vary dramatically. Ecosystems, which are groups of services that work together in a single integrated experience, are becoming more common across industries. Platforms that connect offerings from different industries are also becoming more common.
In an interview with Media 7, Darcy Shapiro, COO of Americas at Cover Genius, talked about the changing expectations of consumers in the insurance industry.
“Consumers expect brands to provide the same high-quality day-to-day experiences directly within the digital platforms they use most. Insurance should be no different.”
Darcy Shapiro, COO of Americas at Cover Genius
The Increasing Acceptance of Parametric Insurance
In contrast to traditional policies, which are paid based on actual loss incurrence, metric insurance has been around for a while, providing payouts when a specific event exceeds an agreed-upon threshold. Previously being used specifically for natural disaster coverage and supplied to countries and large corporations, parametric insurance is making a comeback today. Advancements in sensor technology, data analytics, and Artificial Intelligence (AI in insurance) create broader information indexes on various levels, which opens up parametric risk applications in novel ways.
A reinsurance company recently introduced a parametric water-level insurance product to shield businesses from the financial consequences of high or low river water levels. The program considers measured water levels at specific river gauges and agrees to pay a fixed amount for each day that the index remains below a predetermined threshold value. Other new-generation parametric solutions include terrorism protection for cities and airports, protection for retailers when transit strikes cut down on pedestrian traffic, and help for hotels when there are outbreaks.
The advantages of parametric insurance include faster delivery and avoiding lengthy claims investigations. Furthermore, since parametric products have less uncertainty than traditional insurance, premiums can be significantly lower. In terms of technology, parametric insurance is best suited to blockchain technology, with smart contracts that pay out automatically when certain parameters are met.
A Flood of Data from Connected Devices
Fitness bands, home assistants, smartwatches, and other smart devices are rapidly becoming a part of our daily lives. In addition, smart clothing and medical devices will soon join the fray.
Sensor-equipped equipment has long been common in industrial settings, but the number of connected consumer products is expected to skyrocket in the coming years. Existing gadgets (such as automobiles, fitness trackers, home assistants, smartphones, and smartwatches) will continue to grow. In contrast, new and expanding categories (such as clothing, eyewear, home appliances, medical devices, and shoes) will join them. According to analysts, interconnected devices will reach one trillion by 2025.
The data generated by these devices will result in a flood of new data that carriers can use to understand their customers better, resulting in new product categories, more customized pricing, and an increase in real-time service delivery.
The insurance industry can mine the data generated by these smart devices to better understand their customers’ preferences. This information can also assist insurers in developing new and more personalized product categories.
The Rise of the Insurance Ecosystem
According to McKinsey, insurance ecosystems will generate 30% of global revenue by 2025.
With an expanding array of data sources and a data-driven culture, many insurers will soon be able to plug into and exploit data from complementing firms. These agreements are evolving to involve traditional insurers as well as technology companies. For example, an insurance firm in Europe teamed up with a smart-home technology vendor to improve its home insurance. The latter's technology can detect smoke and carbon monoxide, preventing losses. In addition, a global initiative of a major reinsurance company is developing an ecosystem for InsurTech start-ups and digital distributors. Recent McKinsey research also shows that the insurance business has been having a hard time making efficiency gains for a long time.
Moreover, the operating expense disparity between the best and worst performers in P & C and life has widened over the last decade. Functional excellence, structural simplicity, business transformation, and enterprise agility are four productivity levers that insurers often focus on. Those levers are essential to efficient and productive operations. Ecosystems, which are groups of services that work together, are formed across industries and platforms that connect offerings from different sectors.
Insurers may use ecosystems to integrate their products into seamless client experiences. Ecosystems are essential in today's interconnected world, whether you want to build direct relationships with customers or work with companies that act as the customer interface.
Advancements in Cognitive Technology
Cognition is a critical component of AI in insurance. AI cognitive technologies mimic how the human brain functions. In addition, new technology may make it easier to process huge amounts of data, especially from active insurance products that are linked to specific people.
Carriers can constantly learn and adapt to the world thanks to cognitive technologies. As a result, it can enable insurance companies to introduce new product categories and engagement techniques and respond in real-time to changing underlying risks. In addition, convolutional neural networks and other deep learning technologies, which are currently used primarily for image, audio, and unstructured text processing, will be used in various applications in the future of insurance industry.
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Insurance Technology
Article | July 20, 2022
The pandemic pressed many businesses to go remote. While this enabled employees and their organizations to continue doing business in the face of global uncertainty, the fragility of cybersecurity infrastructure became more apparent than ever. From remote work to a more powerful online presence, cybersecurity threats are a significant challenge for many organizations. With data security, exposure to these threats meant cyber insurance needed to be amped up.
In the race to fortify cybersecurity, small businesses, which have limited resources to train their IT staff, have much catching up to do. As a matter of fact, practically all small businesses maintain sensitive data on their staff, clients, or suppliers, making them open to hacking attempts, malware attacks, digitalfraud, and other online threats. A cyberattack can force a firm to cease operations, incur significant losses, and unanticipated costs, and harm their brand. This is why cyber insurance is so critical.
Here are four things SMBs must understand about cyber insurance and what it covers.
In Case of Data Breaches
Data breaches are one of the most common types of cyberattacks on small firms. Cyber insurance coversthe cost of locating the origin of a data breachand assessing whether the information lost poses any legal obligations. It also includes the price of meeting those obligations, including sending notifications to affected clients, setting up a call center, and providing credit monitoring, as well as the price of hiring legal counsel and paying any fines or penalties.
In Case of Malware Attacks
Ransomware and malware attacks allow criminals to break into an organization’s back-end data. They use it to steal customer information or simply encrypt it which allows them to demand random from the business to reclaim access. Cyber insurance can pay for all of the expenses involved in restoring the system, including recovering data, ransomware removal, vulnerability patching, and, if required, paying the ransom itself. A ransomware attack is the most disruptive,and it may be covered if there is economic loss for the company.
In Case of Phishing and Cyber Fraud
By gaining access to a company's computer system, social engineering letscriminals trick employees intosettlingfictitious bills or diverting cash to their accounts. Businesses may be able to recoup lost funds with the use of cyberinsurance.
Third-Party Coverage
Third-party insurance can shield firms from cyber-related legal troubles, such as government responseor class-action lawsuits brought on by, for instance, unintentional malware spreador the inability to curbunauthorized access to companysystems. It covers all legal expenses, such as settlements and lawyer fees.
What’s the Bottom Line?
Cyber insurance cannot be an alternative to a robust cyber security infrastructure. And small businesses cannot afford to keep vulnerabilities in their systems. Many cyber advice solution providers offer advisory and risk assessment services that may be just what small and medium-sized businesses (SMBs) need to start improving the security of their systems.
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Insurance Technology
Article | May 20, 2022
A quick Google Trends search on data reveals that data analytics, data and analytics, data analysis, and predictive analytics have steadily grown in popularity among businesses across industries.
These terms peaked when business leaders searched for ways to increase ROI and reduce business costs and tech-based investments. The insurance industry is amongst the industries actively leveraging data analytics.
The rising importance of analytics in insurance has made CMOS take note too. As agility became more important in the insurance industry, more than 85% of global businesses shifted to a data-driven model.
The purpose of taking you back is to emphasize that, as a CMO, now you need to churn accurate data and turn it into relevant information. This is a necessary model to practice to make the right decisions or will improve the decision-making process.
Without data analytics, you are deciding in a void, and that’s not considered good practice. Forrester reports that 41% of insurance companies faced challenges in extracting data and making decisions based on it in 2020.
Take a look at how and what you can do with insurance analytics to cater to better insights into your decision-making process and, finally, ROI generation.
Bring Data to These Key Levels of Departments
Marketing
Analytics in insurance raises the bar in terms of marketing. As you know, marketing results frequently fluctuate, making data insights challenging to capture. CMOS who base their decisions solely on outcomes usually loses sight of making sound decisions due to unstructured data.
Therefore, it is essential to have an aligned platform for data analysis in insurance. To begin with, marketers must understand the various types of data analytics available. Most insurance marketers employ descriptive, predictive, and prescriptive analytics, among others. This will assist them in strategizing based on continuous data insights from various sources for any given initiative.
Sales
Sales leaders can also improve how they spend their time by using data analytics to create more accurate sales forecasts. However, the question is, how will they do it efficiently?
CRM software is the answer and solution to them. The software performs best because of its analytical capabilities in combination with data visualization, particularly predictive functions. It generates enormous amounts of data on customer interactions, which can then be used to inform decisions. You can assemble relevant data and use it to make some decisions, such as:
Acquisition and management of leads
Lead segmentation
Sales funnel optimization
There is enormous value in optimizing productive data by focusing on prospects likely to become loyal customers.
Operations
Utilizing data analytics in insurance boosts insurance operations. Small changes help to align a wide range of core processes. You can access data obtained from operations, observe key aspects of the overall processes, and make appropriate decisions. A targeted, timely, and data-driven approach will help you make decisions about these key functions, which can lead to business growth in the long run.
Bain's research in 2019 reports that seventy insurers were polled. They say data analytics will reach 58% in the marketing funnel and 45% in business operations.
Begin with Overcoming Barriers to your Decision-Making Process
Use Data to Identify Customer Patterns
Information from data can identify patterns. As mentioned above in the sales section, CRM's predictive modelling and the popular Google Analytics' descriptive overview are the two best platforms for identifying customer patterns.
What is the best way to get pertinent data? Data mining is the answer to it. Do you want to know about it? Then read data mining for pattern evaluation now!
As a CMO, you're probably aware that behavioral patterns are highly predictable and can sometimes result in unsatisfactory outcomes. This occurs when you are unable to obtain relevant data. And you end up performing ineffective marketing activities. To assist you in overcoming it, an AI-enabled platform can reduce the level of effort and provide the necessary data to study your customers' patterns in real-time. This is how you will notice a significant increase in sales.
According to research by McKinsey and Company, automation saves 43% of insurance employees’ time.
Segmenting Sales Plans
Following the establishment of your customers' patterns, segmenting the insurance sales plan is a necessary step. In this process, analytics provide detailed information about customers, allowing you to make decisions about sales functionalities. This will undoubtedly reduce the time, energy, and effort you previously spent.
Accurate customer segmentation and sales forecasting can also help tailor marketing efforts, improve the sales funnel, and keep sales strategies in check.
When Media 7 contacted Vishal Srivastava, Vice President (Model Validation) at Citi, here’s what he said about data segmentation through data analytics.
CMOs must ensure that adequate data quality checks have been performed, The goal is to ensure a scientific approach to data segmentation, sampling methodology, and data outliers, which can significantly impact revenue forecasts.”
Pricing & Savings
Analytics in insurance marketing can help CMOs make cost-cutting decisions and become more cost-effective in marketing efforts. It can set price ranges based on historical, current, and predictive performance. Also, analytics will help you figure out how to price things in the future, which will be good for ROI.
Keep Improving with Data to Stay Abreast with The Decision-Making Process
Better data organization in your business boosts productivity."
Warren Buffett, an American business magnate, investor, and philanthropist.
This phase is best suited to the current business environment. Implementing data analytics in insurance now will open up tremendous opportunities in the future. To make the most of them, you, as a CMO, must stick to a data-driven model for marketing actions.
Aside from that, it appears that the data analytics you select for your business must be capable of informing and driving performance. Performances ranging from risk assessment to sales forecasting and a plethora of actionable insights assist businesses in thriving.
Frequently Asked Question
How are data analytics used in insurance companies?
Data analytics empowers insurers to optimize each function and also assess risks. It also identifies trustworthy customers, which further boosts engagement.
What does data analytics mean in insurance?
Data analytics empowers insurance professionals by providing them with the business intelligence to understand their customers better, build better products and services, and thus, boost business growth.
How are insurance companies using data?
Insurers can use data to gain insights from customers’ profiles. They can review their history, behavioral pattern, and marketing needs to develop strategies and provide marketing services.
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